Course syllabus

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TEK171 TEK171 Six sigma black belt lp3 VT22 (15 hp)

Course is offered by the department of Technology Management and Economics

Contact details

  • examiner
    • Peter Hammersberg, Dr
  • lecturer
    • Hendry Raharjo, Doc
      • Business analytics | Service Management and Logistic |  Technology Management and Economics | Chalmers
      • hendry.raharjo@chalmers.se
    • Bo Bergman, Prof Em
      • Quality Engineering | Service Management and Logistic |  Technology Management and Economics | Chalmers
  • guest lecturer
    • Sören Knuts, Dr
      • 6sBB | EMS Design for Robustness | GKN Aerospace Engine Systems Sweden
    • Svante Lifvergren, MD, Dr
      • Quality development manager | Skaraborg Hospital 
    • Martin Arvidsson, Dr
      • Quality & After Market Manager | Cochlear Bone Anchored Solutions AB
  • assistent

Course purpose

Six Sigma is a methodology for continual improvements with the purpose to manage sources of variation in relation to the strategic performance requirements of corporations. Six Sigma was first launched by Motorola in 1987. Today, Six Sigma is a leading improvement methodology not only in many manufacturing industries, but also in-service industries such as healthcare, finance, education, and public administration. It is implemented today both as a general investigation methodology for process and product development by itself frequently in many organizations for deeper root-cause analysis and characterization of the underlying system. Six Sigma core objective to contribute to the strategic goals of organizations and is often used in combination with Lean Management.
Within the Six Sigma framework, the improvement activity is driven by a specialist called "Black Belt". The overall purpose of this course is that the students should acquire knowledge and skills corresponding to the standard level of industrial Black Belt. The course is project based with supporting lectures, in which the student should acquire theoretical and practical knowledge and field experience of using the Six Sigma methodology to drive improvement projects. 
Six Sigma is a general framework or methodology for carrying out systematic investigation, process improvements and problem solving, see for example https://en.wikipedia.org/wiki/Six_Sigma. The basic principle is to create a shared understanding of variation and how to mitigate its influence on process or product performance. Six Sigma supports a team or individual in telling when to do what and why in any improvement context. 

Schedule

TimeEdit

Course literature

Course design

The course is structured in two-day sessions. The seven sessions in the black belt course will be planned according to the DMAIC (Define - Measure - Analyse - Improve - Control) cycle. In each of the parts of the course the DMAIC cycle will be followed. Most of the illustrations will be taken from manufacturing environments. Examples of topics for the sessions are: the Six Sigma framework, basic statistics, design of experiments, and Six Sigma in non-manufacturing companies. In the final session there will be a panel discussion with representatives from corporations employing Six Sigma. The Black Belt project will be performed in groups containing 2-3 students (randomly composed) and one external participant that bring an improvement issue from the housing organisation. These participants from industry will also take active part in both sessions and project work. The project’s aim will be to advance the understanding of a problem, develop solution(s) and aids and propose implementation plans makes the organisation develop.

Sessions

Study period 3

Jan - March

Session 1

Understanding Variation

Session 2

Define phase

Session 3

Measure phase

Session 4

Analyze phase

Study period 4

March - June

 

Examination part 1

Session 5

Project review – mid-term presentations

Session 6

Improve phase

Session 7

Control phase

Session 8

Poster session and Project presentations

 

 

Examination part2

 

Supervision and communication with teachers and supervisors regarding projects can be done in class, on scheduled team time, direct communication. Questions and discussions regarding theory and lectures are done in class or in the Q&A section in Canvas.

Software

  • The participants are recommended to bring along their laptops during the sessions (compulsory classroom assignments and exercises will be conducted in class throughout the course).
  • SAS-JMP Pro (Chalmers site license).
    • Main platform for training of Six Sigma tools, data visualisation, data analysis and experimental planing
    • Available:
      • download from student program portal
      • remote access - see separate instructions
  • DOEtrainer
    • Design of experiment will be trained using DOEtrainer simulation software provided in Canvas

Changes made since the last occasion

Adjustment for hybrid teaching

Learning objectives and syllabus

After completion of the course the student should

  • have theoretical and practical knowledge of Six Sigma, its related methodology and tools;
  • be able to actively participate and lead Six Sigma project work;
  • be able to choose and apply relevant tools within the Six Sigma framework to practical problems;
  • be able to critically reflect upon the Six Sigma framework.

Link to the syllabus on Studieportalen: Study plan

Body of knowledge

  • Project scoping
    • Introduction to Six Sigma and Lean concepts
    • Understanding variation
    • Team formation
    • Previous best practices (example of earlier projects)
    • Problem characterisation
      1. Tools for qualitative data analysis (applied AIM)
      2. Software training for graphical data analysis
    • Project definition and scope
      1. Effective SCOPING
      2. Output variable characterisation – improvement target
      3. Project charter
  • Define phase           
    • Voice of the customer
    • Process flow - Value Stream Mapping
    • Literature study
    • Process tampering (Deming’s Funnel experiment)
    • Expected project outcomes
    • Project review on define phase
  • Measure
    • Process mapping
    • Data collection and visualisation
    • Data quality
    • Intro to design of experiments
  • Analyze
    • Process stability and capability analysis
    • Concept of transfer function
    • Basic statistics (p-value, confidence intervals, hypotheses testing, correlation/causation)
    • Quantitative evaluation of influencing factors (Regression analysis, ANOVA
  • Improve
    • Predictive modelling and DOE principles (selection of factors, blocking/ randomization/ replication)
    • Improvement strategies (on-line vs. off-line)
    • Sequential experiments: screening & first-order model building
    • Robust design: parameter and tolerance design
    • Experiments with simulated data
  • Control
    • Process monitoring – control methods
    • Process monitoring with more advanced techniques and charts (EWMA, CUSUM, Moving Average)
    • Initiating change
    • Control plan development and project deliveries

Detailed schedules of the course sessions will be made available to the attendees in the course website early before each session.

Examination

  • Attendance requirement
    • The course participants (master students and external participants) are expected to attend all course sessions. Absence will result in extra assignments to be fulfilled. In particular, for any missed day, the participant will be required to write a two-page report based on a critical review of the literature on the missed topics. To get the final diploma, a minimum of 11 full days of attendance is requested, excluding the project presentation & examination where attendance is always mandatory.
  • Completion of assignments (Instructions and deadlines in separate documents)
    • Group tasks
      • Team project-one page
      • Full factorial group wise reflections
      • Pilgrim Bank Case
      • Project review and opposition, mid-term and final
      • Team diary
        • Content: | Date | Who | What |  (table-format)
    • Individual tasks
      • individual solution on DOE-problem
      • individual reflections
  • Successful completion of the Black Belt project – according to the evaluation criteria in figure 1
    • Final project deliverables – including a business case (i.e the estimated benefits) and other specified deliverables for final seminar.
    • Active discuss of and feedback to neighbouring projects in cluster, both at mid-term and final seminar
  • Individual passing the minimum requirement of DMAIC phase theory exams (>60%) out of max 40 points
    • Sum of two examination parts

Grading and Black Belt certification

  • Grading (U/G)
    • Completion of all parts listed under Examination form
  • Certification as Black Belt
    • Certification means that some field experience of driving improvement projects has been acquired. It is separate from the university grading. It requires passing all points under Examination form AND a personal willingness and drive to contribute to the facilitation and communication within the team and to the organisation, where process development is. In other words, it is possible to pass the course without getting the Black Belt certification even if the rest of team do. The Chalmers Black Belt certification corresponds to the same level of Black Belt knowledge and as the current de facto standard used by industry and institutes (subject to local company variations).

Figure 1

Project evaluation criteria

Course summary:

Date Details Due